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VisRseq: R-based visual framework for analysis of sequencing data.

Hamid Younesy, Torsten Möller, Matthew C Lorincz

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    VisRseq offers a user-friendly framework for sequencing data analysis, enabling biologists to perform complex, interactive analyses without programming skills. This tool integrates R packages and provides a genome browser for enhanced data exploration.

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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Genomics

    Background:

    • Biologists often lack programming expertise for advanced sequencing data analysis.
    • Existing computational tools require significant technical skills, creating a barrier for many researchers.
    • There is a need for accessible tools that bridge the gap between biological interpretation and computational analysis.

    Purpose of the Study:

    • To present VisRseq, an accessible framework for integrative and interactive analysis of sequencing datasets.
    • To empower biologists to conduct complex analyses without requiring programming knowledge.
    • To provide a unified graphical user interface for R packages and Bioconductor repositories.

    Main Methods:

    • Developed VisRseq, a framework utilizing R apps with semi-auto-generated graphical user interfaces.
    • Integrated native apps for interactive exploration, brushing operations, and an integrated genome browser.
    • Enabled chaining of apps to create sophisticated analysis workflows.

    Main Results:

    • VisRseq provides a computationally rich and accessible platform for sequencing data analysis.
    • The framework eliminates the need for programming expertise, democratizing complex analyses.
    • Interactive features and an integrated genome browser enhance data exploration capabilities.

    Conclusions:

    • VisRseq successfully validates its usability for sequencing data analysis through two collaborative case studies.
    • The framework empowers biologists to gain deeper insights from their sequencing data.
    • Case studies demonstrate the practical application and value of VisRseq in biological research.